DocumentCode
2132181
Title
Acoustic surveillance based on Higher-order Local Auto-Correlation
Author
Sasou, Akira
Author_Institution
Nat. Inst. of Adv. Ind. Sci. & Technol. (AIST), Japan
fYear
2011
fDate
18-21 Sept. 2011
Firstpage
1
Lastpage
5
Abstract
The importance of video-surveillance applications has been increasing with the increase of crime and terrorism. In addition to traditional video cameras, the use of acoustic sensors in surveillance and monitoring applications is also becoming increasingly important. In this paper, we apply a High-order Local Auto-Correlation (HLAC) system, which has succeeded in video surveillance application, to extract features from acoustic signals for acoustic-surveillance systems. Experiment results confirmed that the proposed acoustic-surveillance system outperforms a cepstrum-based one under all SNR conditions.
Keywords
acoustic signal processing; acoustic transducers; cepstral analysis; correlation methods; terrorism; video cameras; video surveillance; HLAC system; SNR conditions; acoustic sensors; acoustic signals; acoustic surveillance; acoustic-surveillance systems; cepstrum-based one; crime; high-order local auto-correlation system; higher-order local auto-correlation; monitoring applications; terrorism; video cameras; video-surveillance applications; Cepstrum; Feature extraction; Signal to noise ratio; Surveillance; Time frequency analysis; Vectors; Cepstrum; HLAC; acoustic surveillance;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning for Signal Processing (MLSP), 2011 IEEE International Workshop on
Conference_Location
Santander
ISSN
1551-2541
Print_ISBN
978-1-4577-1621-8
Electronic_ISBN
1551-2541
Type
conf
DOI
10.1109/MLSP.2011.6064587
Filename
6064587
Link To Document